• Title/Summary/Keyword: navigation logic

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FPGA Design of Digital Circuit for TACAN (TACAN을 위한 디지털 회로의 FPGA 구현)

  • Seo, Young-Ho;Choi, Hyun-Jun;Kim, Dong-Wook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.12B
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    • pp.1175-1182
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    • 2010
  • In this paper, we implemented a digital circuit which is targeted on FPGA for estimating azimuth information and distance between aircraft and ground station. All functions for signal processing of TACAN were integrated into a FPGA. The proposed hardware consists of input interface, register file, decoder, signal generator and main controller block. The designed hardware includes a function to generating pulse pair group for azimuth information, a function to responding the interrogation of aircraft for estimating distance between aircraft and ground station, and a function to provide ID information of ground station. The proposed hardware was implemented with FPGA chipset of ALTERA and occupied with 7,071 logic elements.

Reliable Navigation of a Mobile Robot in Cluttered Environment by Combining Evidential Theory and Fuzzy Controller (추론 이론과 퍼지 컨트롤러 결합에 의한 이동 로봇의 자유로운 주변 환경 인식)

  • 김영철;조성배;오상록
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.136-139
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    • 2001
  • This paper develops a sensor based navigation method that utilizes fuzzy logic and the Dempster-Shafer evidence theory for mobile robot in uncertain environment. The proposed navigator consists of two behaviors: obstacle avoidance and goal seeking. To navigate reliably in the environment, we make a map building process before the robot finds a goal position and create a robust fuzzy controller. In this paper, the map is constructed on a two-dimensional occupancy grid. The sensor readings are fused into the map using D-S inference rule. Whenever the robot moves, it catches new information about the environment and replaces the old map with new one. With that process the robot can go wandering and finding the goal position. The usefulness of the proposed method is verified by a series of simulations. This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper.

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Phase Locked Loop based Time Synchronization Algorithm for Telemetry System (텔레메트리 시스템을 위한 PLL 기반의 시각동기 알고리즘)

  • Kim, Geon-Hee;Jin, Mi-Hyun;Kim, Bok-Ki
    • Journal of Advanced Navigation Technology
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    • v.24 no.4
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    • pp.285-290
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    • 2020
  • This paper presents a time synchronization algorithm based on PLL for application to telemetry systems and implement FPGA logic. The large aircraft of the telemetry system acquires status information through each distributed acquisition devices and analyzes the flight status in real time. For this reason, time synchronization between systems is important to improve precision. This paper presents a PLL based time synchronization algorithm that is less complex than other time synchronization methods and takes less time to process data because there is minimized message transmission for synchronization. The validity of proposed algorithm is proved by simulation of Python. And the VHDL logic was implemented in FPGA to check the time synchronization performance.

Collision risk assessment based on the vulnerability of marine accidents using fuzzy logic

  • Hu, Yancai;Park, Gyei-Kark
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.12 no.1
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    • pp.541-551
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    • 2020
  • Based on the trend, there have been numerous researches analysing the ship collision risk. However, in this scope, the navigational conditions and external environment are ignored or incompletely considered in training or/and real situation. It has been identified as a significant limitation in the navigational collision risk assessment. Therefore, a novel algorithm of the ship navigational collision risk solving system has been proposed based on basic collision risk and vulnerabilities of marine accidents. The vulnerability can increase the possibility of marine collision accidents. The factors of vulnerabilities including bad weather, tidal currents, accidents prone area, traffic congestion, operator fatigue and fishing boat operating area are involved in the fuzzy reasoning engines to evaluate the navigational conditions and environment. Fuzzy logic is employed to reason basic collision risk using Distance to Closest Point of Approach (DCPA) and Time of Closest Point of Approach (TCPA) and the degree of vulnerability in the specific coastal waterways. Analytical Hierarchy Process (AHP) method is used to obtain the integration of vulnerabilities. In this paper, vulnerability factors have been proposed to improve the collision risk assessment especially for non-SOLAS ships such as coastal operating ships and fishing vessels in practice. Simulation is implemented to validate the practicability of the designed navigational collision risk solving system.

Development of a System for Transmitting a Navigator's Intention for Safe Navigation

  • Hong, Taeho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.2
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    • pp.130-135
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    • 2014
  • For the past three decades, ship-to-ship collision accidents have steadily increased on the coast of South Korea by about 20% annually. Marine accidents have become more likely and more devastating in areas with increasing marine traffic and rising numbers of high-speed ships. Over 30% of the marine accidents in South Korea are concentrated in spring, since Korea's coast is often covered in dense fog at this time of the year. Fog is generated when a large temperature range exists within a day, and this daily temperature range has increased due to abnormal weather conditions. This research proposed a system for transmitting a navigator's intention utilizing electronic methods. A navigator's intention was expressed on the electronic navigation chart for easier understanding of the surrounding situation, and the effectiveness of the system was verified through practical tests.

Fuzzy Inference Based Collision Free Navigation of a Mobile Robot using Sensor Fusion (퍼지추론기반 센서융합 이동로봇의 장애물 회피 주행기법)

  • Jin, Taeseok
    • Journal of the Korean Society of Industry Convergence
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    • v.21 no.2
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    • pp.95-101
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    • 2018
  • This paper presents a collision free mobile robot navigation based on the fuzzy inference fusion model in unkonown environments using multi-ultrasonic sensor. Six ultrasonic sensors are used for the collision avoidance approach where CCD camera sensors is used for the trajectory following approach. The fuzzy system is composed of three inputs which are the six distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot's wheels, and three cost functions for the robot's movement, direction, obstacle avoidance, and rotation. For the evaluation of the proposed algorithm, we performed real experiments with mobile robot with ultrasonic sensors. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

Hierarchical Behavior Control of Mobile Robot Based on Space & Time Sensor Fusion(STSF)

  • Han, Ho-Tack
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.4
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    • pp.314-320
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    • 2006
  • Navigation in environments that are densely cluttered with obstacles is still a challenge for Autonomous Ground Vehicles (AGVs), especially when the configuration of obstacles is not known a priori. Reactive local navigation schemes that tightly couple the robot actions to the sensor information have proved to be effective in these environments, and because of the environmental uncertainties, STSF(Space and Time Sensor Fusion)-based fuzzy behavior systems have been proposed. Realization of autonomous behavior in mobile robots, using STSF control based on spatial data fusion, requires formulation of rules which are collectively responsible for necessary levels of intelligence. This collection of rules can be conveniently decomposed and efficiently implemented as a hierarchy of fuzzy-behaviors. This paper describes how this can be done using a behavior-based architecture. The approach is motivated by ethological models which suggest hierarchical organizations of behavior. Experimental results show that the proposed method can smoothly and effectively guide a robot through cluttered environments such as dense forests.

Development of an Intelligent and Hybrid Scheme for Rapid INS Alignment

  • Huang, Yun-Wen;Chiang, Kai-Wei
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.115-120
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    • 2006
  • This article propose a new idea of developing a hybrid scheme to achieve faster INS alignment with higher accuracy using a novel procedure to estimate the initial attitude angles that combines a Kalman filter and Adaptive Neuro-Fuzzy Inference System architecture. A tactical grade inertial measurement unit was applied to verify the performance of proposed scheme in this study. The preliminary results indicated the outstanding improvements in both time consumption for fine alignment process and accuracy of estimated attitude angles, especially in heading angles. In general, the improvement in terms of time consumption and the accuracy of estimated attitude estimated accuracy reached 80% and 70% respectively during alignment process after compensating the attitude angles estimated by an extended Kalman filter with 15 states using proposed approach. It is worth mentioned that the proposed approach can be implemented in general real time navigation applications.

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Evolvable Neural Networks Based on Developmental Models for Mobile Robot Navigation

  • Lee, Dong-Wook;Seo, Sang-Wook;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.176-181
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    • 2007
  • This paper presents evolvable neural networks based on a developmental model for navigation control of autonomous mobile robots in dynamic operating environments. Bio-inspired mechanisms have been applied to autonomous design of artificial neural networks for solving practical problems. The proposed neural network architecture is grown from an initial developmental model by a set of production rules of the L-system that are represented by the DNA coding. The L-system is based on parallel rewriting mechanism motivated by the growth models of plants. DNA coding gives an effective method of expressing general production rules. Experiments show that the evolvable neural network designed by the production rules of the L-system develops into a controller for mobile robot navigation to avoid collisions with the obstacles.

The Navigation Control for Intelligent Robot Using Genetic Algorithms (유전알고리즘을 이용한 지능형 로봇의 주행 제어)

  • Joo, Young-Hoon;Cho, Sang-Kyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.4
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    • pp.451-456
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    • 2005
  • In this paper, we propose the navigation control method for intelligent robot using messy genetic algorithm. The fuzzy controller design for navigation of the intelligent robot was dependant on expert's knowledge. But, the parameters of the fuzzy logic controller obtained from expert's control action may not be outimal. In this paper, to solve the above problem, we propose the identification method to automatically tune the number of fuzzy rule and parameters of memberships of fuzzy controller using mGA. Finally, to show and evaluate the generality and feasibility of the proposed method, we provides some simulations for wall following navigation of intelligent robot.